Advances in River Engineering
Online ISSN : 2436-6714
DEVELOPMENT OF NOWCAST CORRECTION METHOD FOR ENSAMBLE RAILNFALL PREDICTION USING DEEP LEARNING
Masaya YAMAMOTO, Aritoshi MASUDA
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JOURNAL FREE ACCESS

2020 Volume 26 Pages 61-64

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Abstract

In this study, we developed nowcast correction method for ensemble rainfall prediction using deep learning. We adopted convolutional lstm neural network for rainfall prediction model. Our model’s parameter has updated by past 4 years observed radar and MSM (Meso-scale Model) datasets . Furthermore, we applied our model to all ensemble member of MEPS (Meso-scale Ensemble Prediction System) rainfall prediction provided by JMA (Japan Meteorological Agency).

As a result, corrected rainfall prediction's MAE (Mean Absolute Error) has improved. Moreover, ensemble member's range of corrected MEPS can hold observed rainfall.

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© 2020 Japan Society of Civil Engineers
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